Difference Between Cloud Computing and Grid Computing

Cloud Computing and Grid Computing are both forms of distributed computing. What do these approaches share in common and what are the differences?

Traditionally, computers use a local server or the hard disk in a personal computer to manage and process data. Cloud Computing is a radically new concept that leverage the power of internet to process and store data from a network of remote servers located anywhere in the world.

Grid computing, in contrast refers to combining or pooling computer resources from multiple domains to manage and process data. It is an extension of the conventional cluster computing concept.
Common Features between Grid and Cloud Computing

There is apparently only a thin line of difference separating cloud computing and grid computing, and these terms find use interchangeably in common parlance. Both methods are ways of distributed computing, or computing using remote resources over a network aimed at optimizing use of resources.
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Features common to both cloud and grid computing include:
Heavy use of abstraction, or masking the actual complex process taking place inside the system, and instead providing users with a simpler and easy to use interface
Scalability, or varying computing loads according to load demands. Both clouds and grids tend to draw more resources from the pool when the processes need so, and surrender the capacity or resources not needed to the common pool, for other users
Multi-tenancy and multitask, or the the ability to perform many different tasks simultaneously.

Differences between Grid and Cloud Computing

Although cloud computing and grid computing have much in common, they remain two different concepts. The major differences follow:
The major difference is in the architecture or modus-operandi. Cloud computing divides large tasks into chunks or small portions, disburse these portions across many machines for simultaneous processing, and then gather all of it. Grid computing on the other hand uses the best resource available from the pool without breaking up tasks. Local resources undertake the processing at the grid site, and wait in queue for access to the resource.
In clouds, the location of the processing center remain hidden, whereas in grids this is transparent, and users even have the option of selecting the location based on the list of available resources.
Grids operate in a project-oriented model, to address large-scale computing problems. Clouds, on the other hand address internet-scale computing problems.

Cloud computing and grid computing are not mutually exclusive, and many organizations use both together to speed up tasks. For instance, organizations use grid computing to select the best available resource to perform a task, and then apply cloud computing to execute the task faster using the different devices available within such resource.